A variable speed constant frequency wind turbine generator performs maximum wind energy tracking while operating with a rated wind speed, captures the maximum wind energy from natural wind and converts it into electricity and transfers into a power grid. In order to capture the maximum wind energy, the rotating speed ω, must be adjusted to the optimum value ω*r when the wind speed changes, and the optimal tip speed ratio λopt is kept, that is, the process of maximum wind energy tracking can be construed as a rotating speed adjusting process of a wind turbine. The effect of maximum wind energy tracking depends on rotating speed adjusting performance. In a turbulent wind field, λopt is kept constant only if the torque of a generator changes fast. However, if the mechanical torque changes too fast, vibration of the system is enhanced, increasing the risk of fatigue damage and reducing service life of the system. Therefore, during maximum wind energy tracking, consideration must be given to both mechanical load of the wind turbine generator and control of the mechanical torque to reduce rate of change of the mechanical torque when the wind speed changes. The traditional maximum wind energy tracking method comprises an optimal tip speed ratio method, a hill climbing method and a power feedback method. Using the optimal tip speed ratio method to perform the maximum wind energy tracking, the optimal rotating speed value corresponding to the optimal tip speed ratio is calculated, as the reference instruction of the control system, from the measured wind speed and the rotating speed of the generator. This method has simple control structure and is easy to implement, but the disadvantage is that it requires real-time accurate wind speed measurement, which is hard to realize in the actual wind field. The hill climbing method judges the variation trend of the rotating speed by measuring the rotating speed and the output power of the wind turbine in real time and according to their change of gradient, and controls the operating point of the unit to approach the maximum power point. This method avoids the problem of wind speed measurement, but it requires measuring the gradient of the output power and the rotating speed of the wind turbine in real time, and a gradient sensor makes louder noise and is unstable at a high frequency. Moreover, the time for measuring and judging will affect the accuracy of algorithm. The power feedback method controls the electromagnetic torque of a double-fed motor by controlling the output active power of the double-fed motor, thereby indirectly controlling the rotating speed of the unit. This method can efficiently avoid fluctuation of the output power and also does not require detection of the wind speed. The disadvantage of this method is that it requires simulation and experiment to obtain the power-wind speed curve with different curves for different wind wheels. For the disadvantages of the traditional control method, some of the control methods in the modern control theory are introduced into the maximum wind energy tracking. Predictive Control: wind energy prediction is performed for maximum wind energy, the wind speed is predicted by using a support vector regression (SVR) algorithm, and the predicted wind speed is input into a wind energy converting system to calculate the optimal rotating sped value at the wind speed; this method does not require wind speed measurement and the disadvantage is that the accuracy for wind energy prediction is not high; Neural Network Control: The WRBFN neural network is combined with the hill climbing algorithm, and a controller is designed by using a particle swarm optimization algorithm; this method efficiently solves the shortage of the hill climbing algorithm and is only suitable for a permanent magnet motor but not in a double-fed motor, i.e., the method has a small range of application; Nonlinear Control: The sliding mode variable structure control is applied to wind power generation, a switching surface is defined as the power relative error, and different sliding mode control rates are respectively employed to normal and stall modes of the generator so as to achieve the aim of no error tracking and maximum wind energy capturing; this method has fast response speed, but the theory is based on and is too dependent on the accurate mathematic model of the object; Fuzzy Control: The maximum wind energy tracking is performed by using the fuzzy control, which overcomes the disadvantage of the traditional control of being dependent on the accurate mathematic model of the controlled object and has a problem that the designed controller has low accuracy; and Adaptive Control: The extremum seeking control based on perturbation is applied to the maximum wind energy tracking in wind power, and the change of the wind speed is processed in the wind energy converting system to obtain an excitation signal so as to obtain the optimal top speed ratio, thereby reaching the maximum capturing rate for the wind energy; this method does not require establishment of an accurate model for the controlled object, and it has fast control speed and high accuracy, but the disadvantage of the method is the same as that of the optimal tip speed ratio method, i.e., it requires real-time accurate measurement of the wind speed. The sliding mode variable structure control is combined with the extremum seeking control. Based on the sliding mode extremum seeking control, the control method has advantages of simple structure and unique input variable.